Assignment 9 - plotly (15 pts)

library(tidyverse)

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## ✔ readr   2.1.2      ✔ forcats 0.5.2

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library(plotly)

## 
## Attaching package: 'plotly'
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data <- as.data.frame(iris)
head(data)

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

create a scatterplot of petal length vs petal width colored by species using ggplot2. Set you colors manually.

p1 <- ggplot(data, aes(Petal.Length, Petal.Width)) +
  geom_point(aes(color = Species), position = 'jitter') +
  scale_color_manual(values = c('#7B435B', '#9FA0C3', '#BCF8EC')) +
  theme_minimal() +
  ylab('Petal Width') +
  xlab('Petal Length') +
  theme(panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank())


p1

Convert your plot above to an interactive graph using ggplotly

ggplotly(p1)

Now code the the above plot directly in plot_ly

1. Manipulate data as needed

setosa <- data %>% filter(Species == 'setosa')
versicolor <- data %>% filter(Species == 'versicolor')
virginica <- data %>% filter(Species == 'virginica')

2. initialize your plotly plot

p2 <- plot_ly(type = 'scatter', mode = 'markers') 

3. add your Setosa trace

p2 <- p2 %>%
  add_trace(
    x = setosa$Petal.Length,
    y = setosa$Petal.Width,
    marker = list(
      color = '#7B435B',
      size = 10),
    name = 'Setosa'
  ) 
p2

4. Add your versicolor trace

p2 <- p2 %>%
  add_trace(
    x = versicolor$Petal.Length,
    y = versicolor$Petal.Width,
    marker = list(
      color = '#9FA0C3',
      size = 10),
    name = 'Versicolor'
  ) 

p2

5. Add your virginica trace

p2 <- p2 %>%
  add_trace(
    x = virginica$Petal.Length,
    y = virginica$Petal.Width,
    marker = list(
      color = '#BCF8EC',
      size = 10),
    name = 'Virginica'
  ) 

p2

6. Update the tooltip to read petal width: x.x petal length: x.x

p2 <- plot_ly(type = 'scatter', mode = 'markers') 

p2 <- p2 %>%
  add_trace(
    x = setosa$Petal.Length,
    y = setosa$Petal.Width,
    marker = list(
      color = '#7B435B',
      size = 10),
    name = 'Setosa',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x}'
  ) 

p2 <- p2 %>%
  add_trace(
    x = versicolor$Petal.Length,
    y = versicolor$Petal.Width,
    marker = list(
      color = '#9FA0C3',
      size = 10),
    name = 'Versicolor',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x}'
  ) 

p2 <- p2 %>%
  add_trace(
    x = virginica$Petal.Length,
    y = virginica$Petal.Width,
    marker = list(
      color = '#BCF8EC',
      size = 10),
    name = 'Virginica',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x}'
  ) 

p2

7. Add graph title and remove the gridlines

p2 <- plot_ly(type = 'scatter', mode = 'markers') 

p2 <- p2 %>%
  add_trace(
    x = setosa$Petal.Length,
    y = setosa$Petal.Width,
    marker = list(
      color = '#7B435B',
      size = 10),
    name = 'Setosa',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x}'
  ) 

p2 <- p2 %>%
  add_trace(
    x = versicolor$Petal.Length,
    y = versicolor$Petal.Width,
    marker = list(
      color = '#9FA0C3',
      size = 10),
    name = 'Versicolor',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x}'
  ) 

p2 <- p2 %>%
  add_trace(
    x = virginica$Petal.Length,
    y = virginica$Petal.Width,
    marker = list(
      color = '#BCF8EC',
      size = 10),
    name = 'Virginica',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x}'
  ) 

p2 <- p2 %>%
  layout(title = 'Scatterplot of Petal Length by Petal Width',
         xaxis = list(title = 'Petal Length', showgrid = F),
         yaxis = list(title = 'Petal Width', showgrid = F, zeroline = F))
        

p2

Homework:

9. Take the above graph and make it 3D by adding Sepal Length on the z-axis.

# Referenced plotly-1.html from class to complete this
p3 <- plot_ly(type = 'scatter3d', mode = 'markers')  

p3 <- p3 %>%
  add_trace(
    x = setosa$Petal.Length,
    y = setosa$Petal.Width,
    z = setosa$Sepal.Length,
    marker = list(
      color = '#E389B9',
      size = 10,
      line = list(
        color = 'lightgray',
        width = .5
      )
      ),
    name = 'Setosa',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x} <br>Sepal Length: %{z}'
  ) 

p3 <- p3 %>%
  add_trace(
    x = versicolor$Petal.Length,
    y = versicolor$Petal.Width,
    z = versicolor$Sepal.Length,
    marker = list(
      color = '#288BA8',
      size = 10,
      line = list(
        color = 'lightgray',
        width = .5
      )),
    name = 'Versicolor',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x} <br>Sepal Length: %{z}'
  ) 

p3 <- p3 %>%
  add_trace(
    x = virginica$Petal.Length,
    y = virginica$Petal.Width,
    z = virginica$Sepal.Length,
    marker = list(
      color = '#746AB0',
      size = 10,
      line = list(
        color = 'lightgray',
        width = .5
      )),
    name = 'Virginica',
    hovertemplate = 'Petal Width: %{y} <br>Petal Length: %{x} <br>Sepal Length: %{z}'
  ) 

p3 <- p3 %>%
  layout(title = 'Scatterplot of Petal Length by Petal Width by Sepal Length',
         scene = list(xaxis = list(title = "Petal Length"),
                      yaxis = list(title = "Petal Length"),
                      zaxis = list(title = "Sepal Length")))
        

p3

10. Create grouped boxplots where each iris dataset measure in on the x-axis with 3 boxplots for each measure representing the species. Use your own cohesive color palette using coolors.co. Don’t forget to include all the parts of a chart.

# Sites referenced to complete this code (though none of it is copied or a "chunk" of code):
# https://plotly.com/r/box-plots/#grouped-box-plots
# https://www.geeksforgeeks.org/how-to-create-grouped-box-plot-in-plotly/
# https://www.rdocumentation.org/packages/plotly/versions/4.10.0/topics/add_trace

p4 <- plot_ly(type = 'box') 

x1 = c(replicate(50, 'Petal Length'), replicate(50, 'Petal Width'), replicate(50, 'Sepal Length'))

p4 <- p4 %>% add_trace(
    type='box',
    x = x1,
    y = c(versicolor$Petal.Length, versicolor$Petal.Width, versicolor$Sepal.Length),
    color = '#482C3D',
    name = 'Versicolor'
  ) 
p4 <- p4 %>%
  add_trace(
    type='box',
    x = x1,
    y = c(setosa$Petal.Length, setosa$Petal.Width, setosa$Sepal.Length),
    color = '#537D8D',
    name = 'Setosa'
  ) 
p4 <- p4 %>%
  add_trace(
    type='box',
    x = x1,
    y = c(virginica$Petal.Length, virginica$Petal.Width, virginica$Sepal.Length),
    color = '#E5D352',
    name = 'Virginica'
  ) 

p4 <- p4 %>%
  layout(title = 'Grouped Boxplot of Petal Length, Petal Width, and Sepal Length by Species', boxmode='group', xaxis = list(showgrid = F, zeroline = T),
         yaxis = list(title = 'Centimeters', showgrid = F, zeroline = T))

p4

## Warning: Can't display both discrete & non-discrete data on same axis

## Warning: 'layout' objects don't have these attributes: 'boxmode'
## Valid attributes include:
## '_deprecated', 'activeshape', 'annotations', 'autosize', 'autotypenumbers', 'calendar', 'clickmode', 'coloraxis', 'colorscale', 'colorway', 'computed', 'datarevision', 'dragmode', 'editrevision', 'editType', 'font', 'geo', 'grid', 'height', 'hidesources', 'hoverdistance', 'hoverlabel', 'hovermode', 'images', 'legend', 'mapbox', 'margin', 'meta', 'metasrc', 'modebar', 'newshape', 'paper_bgcolor', 'plot_bgcolor', 'polar', 'scene', 'selectdirection', 'selectionrevision', 'separators', 'shapes', 'showlegend', 'sliders', 'spikedistance', 'template', 'ternary', 'title', 'transition', 'uirevision', 'uniformtext', 'updatemenus', 'width', 'xaxis', 'yaxis', 'barmode', 'bargap', 'mapType'